ReddRadar
Topic: multi-agent-systems
352 skills in this topic.
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release
Automated release workflow for oh-my-claudecode
Yeachan-Heo/oh-my-claudecode 28,047
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sciomc
Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode
Yeachan-Heo/oh-my-claudecode 28,047
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setup
Use first for install/update routing — sends setup, doctor, or MCP requests to the correct OMC setup flow
Yeachan-Heo/oh-my-claudecode 28,047
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skill
Manage local skills - list, add, remove, search, edit, setup wizard
Yeachan-Heo/oh-my-claudecode 28,047
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team
N coordinated agents on shared task list using Claude Code native teams
Yeachan-Heo/oh-my-claudecode 28,047
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trace
Evidence-driven tracing lane that orchestrates competing tracer hypotheses in Claude built-in team mode
Yeachan-Heo/oh-my-claudecode 28,047
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ultraqa
QA cycling workflow - test, verify, fix, repeat until goal met
Yeachan-Heo/oh-my-claudecode 28,047
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ultrawork
Parallel execution engine for high-throughput task completion
Yeachan-Heo/oh-my-claudecode 28,047
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visual-verdict
Structured visual QA verdict for screenshot-to-reference comparisons
Yeachan-Heo/oh-my-claudecode 28,047
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writer-memory
Agentic memory system for writers - track characters, relationships, scenes, and themes
Yeachan-Heo/oh-my-claudecode 28,047
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data-analysis
Patterns for data loading, exploration, and statistical analysis
Yeachan-Heo/My-Jogyo 162
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experiment-design
Best practices for designing reproducible experiments
Yeachan-Heo/My-Jogyo 162
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ml-rigor
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
Yeachan-Heo/My-Jogyo 162
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data-analysis
Patterns for data loading, exploration, and statistical analysis
Yeachan-Heo/My-Jogyo 162
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experiment-design
Best practices for designing reproducible experiments
Yeachan-Heo/My-Jogyo 162
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ml-rigor
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
Yeachan-Heo/My-Jogyo 162